CN111415261B - Control method, system and device for dynamically updating flow control threshold of bank system - Google Patents
Control method, system and device for dynamically updating flow control threshold of bank system Download PDFInfo
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Abstract
The invention discloses a control method, a system and a device for dynamically updating a flow control threshold of a banking system, wherein the control method comprises the following steps: for each node, acquiring the actual transaction completion amount of the transaction received by the node in the historical flow control period; classifying the transactions to obtain the actual transaction amount of all types of transactions; acquiring a flow control threshold value of a current flow control period according to the actual transaction amount of each type of transaction by a preset threshold value calculation method; and dynamically updating according to the flow control threshold. According to the invention, by self-calculation on each node, the overall risk brought by calculation and distribution of the unified service center is avoided; meanwhile, calculation is carried out on each node based on actual transaction conditions, and under the advantages of more sensitive static flow control and faster recovery speed, the condition that the flow control threshold of a single transaction node is unreasonably set and the whole transaction line is affected is reduced to the greatest extent.
Description
Technical Field
The present invention relates to the field of computer application technologies, and in particular, to a control method, system, and apparatus for dynamically updating a flow control threshold of a banking system.
Background
Currently, online transaction systems generally employ a distributed architecture, where multiple servers process transactions simultaneously, and one or more database servers are used to store transaction data. In order to prevent the application system from being flushed by an instantaneous flow peak, and ensure high availability and transaction consistency of the application, the on-line transaction system is generally controlled according to indexes such as the concurrent thread number of the application, TPS (Transactions Per Second, number of transactions that can be processed per second) and the like. The transaction flow control mechanism used by the bank system is similar to the distributed system flow control method, and is mainly based on static flow control based on concurrent thread number and is assisted by a dynamic flow control method based on transaction processing time.
However, the traditional static flow control adopts a pre-allocation mode, the static flow control threshold values are all obtained by manual calculation, when application service is deployed, the QPS (Querys Per Second query rate per second) threshold value allocated by each service node is calculated by the application according to the number of cluster service nodes and the static flow control threshold values, when the system operates, each service node carries out flow control according to the threshold value allocated by itself, and access is refused for requests exceeding the flow control threshold value. The traditional static flow control strategy cannot be suitable for the scene that the service instance changes, if the number of the service instance changes, the statically allocated QPS needs to be dynamically adjusted in real time, otherwise, flow control inaccuracy is caused.
To address the drawbacks of static allocation, dynamic quota allocation is often employed in practice to assist. The working principle is as follows: the service registration center dynamically pushes the flow control threshold QPS of each service node by taking the flow control period T as a unit. When the service node is changed, the service registration center is triggered to recalculate the quota of each node and push, so that whether the number of the service node is increased or decreased, the service node can be identified and processed in the next flow control period, and the problem that the static allocation scheme cannot adapt to the dynamic change of the number of the nodes is solved.
However, the dynamic quota allocation system is based on the service registry to complete calculation and allocation of the flow control threshold, which may cause excessive pressure of the service registry for banking systems with complex transaction types, and may become a bottleneck for the whole system. Meanwhile, the dynamic quota allocation control aims at the flow control of the QPS, the QPS threshold is averagely allocated to the nodes with the same function, certain transaction services of the banking system have millions of transaction quantity per minute, the requirements on the system performance are high, the quick recovery after the flow control is generated is important, the trigger conditions used by the traditional dynamic flow control algorithm are mainly system processing time, system response time and the like, and the perception of the system resource index is lagged.
In addition, a bank system usually completes a transaction by a plurality of simple service combinations, the transaction calling path is long, the traditional concurrent flow control threshold setting is not considered from the perspective of the whole transaction line, and the concurrent quantity configuration of each computing node is not reasonable.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a control method, a system and a device for dynamically updating the flow control threshold of a banking system, which can reasonably set the flow control threshold of each node and perform the dynamic updating.
According to an embodiment of the present invention, there is provided a control method for dynamically updating a flow control threshold of a banking system, the banking system including a plurality of system components, each system component serving as a node of the banking system to perform a different transaction process, the control method including: for each node, acquiring the actual transaction completion amount of the transaction received by the node in the historical flow control period; classifying the transactions to obtain the actual transaction amount of all types of transactions; acquiring a flow control threshold value of a current flow control period according to the actual transaction amount of each type of transaction by a preset threshold value calculation method; and dynamically updating according to the flow control threshold.
In some embodiments of the invention, the classifying the transaction comprises: the transactions are categorized according to the different sources of the transactions.
In some embodiments of the present invention, the obtaining, by a preset threshold calculation method, the flow control threshold of the current flow control period according to the actually completed transaction amounts of the various transactions includes:
acquiring a weight value corresponding to the previous flow control period of the current flow control period;
acquiring the actual transaction amount of the various transactions corresponding to the previous flow control period;
the weight value and the actual transaction amount of all the transactions are put into a pre-constructed threshold value acquisition model, and the flow control threshold value of the current flow control period is acquired;
wherein the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,the actual transaction amount of the j-th transaction received in the i-1-th flow control period is completed.
In some embodiments of the present invention, the obtaining, by a preset threshold calculation method, the flow control threshold of the current flow control period according to the actually completed transaction amounts of the various transactions includes:
the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
the actual transaction amount group of each type of transaction corresponding to the previous k flow control periods of the current flow control period i is obtained, and the actual transaction amount group is expressed as follows:
the weight value group and the actually completed transaction amount group of various transactions are put into a pre-constructed threshold value acquisition model to acquire a flow control threshold value of the current flow control period;
the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
In some embodiments of the invention, the weight value is obtained by means of machine learning.
Meanwhile, the embodiment of the invention also provides a control system for dynamically updating the flow control threshold of a banking system, the banking system comprises a plurality of system components, each system component is used as a node of the banking system to finish different transaction processing, and the control system comprises: the data acquisition module is used for acquiring the actual transaction amount of the transaction received by each node in the historical flow control period; the classification module is used for classifying the transactions and acquiring the actual transaction amount of various transactions; the threshold value acquisition module is used for acquiring a flow control threshold value of the current flow control period according to the actual transaction amount of the various transactions by a preset threshold value calculation method; and the self-updating module is used for dynamically updating according to the flow control threshold value.
In some embodiments of the invention, the categorization module categorizes the transaction according to the source of the transaction.
In some embodiments of the invention, the threshold acquisition module is configured to:
acquiring a weight value corresponding to the previous flow control period of the current flow control period;
acquiring the actual transaction amount of the various transactions corresponding to the previous flow control period;
the weight value and the actual transaction amount of all the transactions are put into a pre-constructed threshold value acquisition model, and the flow control threshold value of the current flow control period is acquired;
the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,for reception in the i-1 th flow control periodThe actual amount of completed transactions for the j-th class of transactions.
In some embodiments of the invention, the threshold acquisition module is configured to:
the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
the actual transaction amount group of each type of transaction corresponding to the previous k flow control periods of the current flow control period i is obtained, and the actual transaction amount group is expressed as follows:
the weight value group and the actually completed transaction amount group of various transactions are put into a pre-constructed threshold value acquisition model to acquire a flow control threshold value of the current flow control period;
the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
In some embodiments of the invention, the weight value is obtained by means of machine learning.
In addition, the embodiment of the invention provides a control device for dynamically updating the flow control threshold value of a banking system, which comprises a memory and a processor, wherein the memory is used for storing computer readable instructions; the processor is configured to execute the computer readable instructions to implement the method of any of the preceding embodiments.
The embodiment of the invention also provides a computer storage medium storing a computer program which, when executed by a processor, implements the method according to any one of the preceding embodiments.
According to the invention, by self-calculation on each node, the overall risk brought by calculation and distribution of the unified service center is avoided; meanwhile, calculation is carried out on each node based on actual transaction conditions, and under the advantages of more sensitive static flow control and faster recovery speed, the condition that the flow control threshold of a single transaction node is unreasonably set and the whole transaction line is affected is reduced to the greatest extent.
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In order to facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings.
FIG. 1 is a partial abstract view of a banking system;
FIG. 2 is a flow diagram of a control method for dynamically updating a flow control threshold of a banking system, in accordance with one embodiment of the present invention;
FIG. 3 is a flow diagram of one embodiment of process 102 of FIG. 1;
FIG. 4 is a flow diagram of another embodiment of process 102 of FIG. 1;
fig. 5 is a block diagram of a control system for dynamically updating flow control thresholds for a banking system in accordance with one embodiment of the present invention.
Detailed Description
Various aspects of the invention are described in detail below with reference to the drawings and detailed description. Well-known modules, units, and their connections, links, communications, or operations between each other are not shown or described in detail. Also, the described features, architectures, or functions may be combined in any manner in one or more implementations. It will be appreciated by those skilled in the art that the various embodiments described below are for illustration only and are not intended to limit the scope of the invention. It will be further appreciated that the modules or units or processes of the embodiments described herein and illustrated in the drawings may be combined and designed in a wide variety of different configurations.
First, nouns and abbreviations related to the embodiments of the present invention will be explained:
flow Control: flow control refers to a method for controlling the number of transactions sent and received by a node of a banking system in order to ensure that a server operates normally. The flow control can avoid system breakdown caused by system overload or impact of malicious requests to the system, and is an effective means for preventing and recovering faults in the service peak period.
Flow control period: and the T is the time span for the flow control to re-acquire various indexes and re-calculate the flow control threshold.
QPS: querys Per Second, the rate of queries per second, is the number of queries a server can respond to per second, and is a measure of how much traffic a particular query server is handling in a given time.
TPS: transactions Per Second, the number of transactions that a server can process per second, is the unit of measure of the software test results. A transaction refers to the process in which a client sends a request to a server and the server then reacts, and typically contains multiple queries.
KPI: key Performance Indicator, key performance indicators.
In the embodiment of the invention, TPS refers to the number of transactions processed by a server per second, KPI refers to performance data of a service node, and mainly refers to the rate at which the service node processes transactions.
Banking systems are typically made up of multiple system components that each perform different transaction processing functions by combining transactions. Fig. 1 shows a partial abstract view of a banking system, referring to fig. 1, nodes a, b, c, m, n, g, n, x, y, z each represent a system component node, a node is used as a service end, a concurrent thread number threshold of an external service interface is represented by F, and a concurrent threshold of a backward call is represented by R as a service consumer.
Taking a component node d as an example, the d node provides interface method call of d1, d2 and d3 services to the outside, wherein a and b nodes call d1 service interfaces, c nodes call d2 and d3 service interfaces, the concurrent execution number calling the three service interfaces is controlled on the d node, and when the concurrent execution number exceeds a set threshold F d1 、F d2 、F d3 And when the flow control is abnormal, the flow control abnormality is thrown out.
Similarly, the d node also serves as a service consumer to call the back-end service, the m node m1 and m2 services are called, and the concurrency number threshold of the m1 and m2 services is R d1,m1 、R d2,m2 Calling n node n1 service, wherein the concurrency number threshold value of the n1 service is R d3,n1 Both the d node and the y node invoke the z1 service of the z node.
For banking systems, the flow control threshold is typically set according to the KPI of the node. Taking node d as an example, the flow control threshold at least meets the following condition:
(1) The flow control threshold is at least 1, i.e. F di ≥1,R di,** ≥1。
(2) When the node d is used as a service end, the sum of the maximum flow control threshold values of the provided services is smaller than the maximum connection number supported by the performance of the node, namely:
(3) The setting proportion of the maximum flow control threshold value of each service provided by the node should be matched with the proportion of the transaction number actually generated by each service, if the fluctuation range of the transaction number actually generated by each service is not large, the setting proportion of the maximum flow control threshold value of each service should be equal to the proportion of the average transaction number in a certain time period of each service, namely:
(4) When the node d is used as a consumption end, the maximum flow control threshold of other services is called outwards and is smaller than the maximum thread number which can be received by the called service interface, namely:
R **,di ≤F di
in an embodiment of the present invention, only the flow control threshold when the node is the server is considered. However, even if only the flow control threshold value when the node is taken as the server is considered, for a banking system with complex transaction types, the traditional dynamic quota allocation system may cause excessive pressure of the service registry, which becomes a bottleneck of the whole system, and the static flow control cannot cope with changeable system environments.
In this regard, an embodiment of the present invention provides a control method for dynamically updating a flow control threshold of a banking system, as shown in fig. 2, where the method includes:
100: for each node, acquiring the actual transaction completion amount of the transaction received by the node in the historical flow control period;
101: classifying the transactions to obtain the actual transaction amount of all types of transactions;
102: acquiring a flow control threshold value of a current flow control period according to the actual transaction amount of various transactions by a preset threshold value calculation method;
103: and dynamically updating according to the flow control threshold.
In embodiments of the present invention, transactions may be categorized according to the different sources of the transactions.
Therefore, for each node, the flow control threshold value of the node is autonomously calculated according to the actual transaction condition, so that the advantages of more sensitive static flow control and faster recovery speed can be maintained, and the flow control threshold value can be set more reasonably.
In an embodiment of the present invention, the process 102 may be performed in the following manner, referring to fig. 3, specifically including:
104: acquiring a weight value corresponding to the previous flow control period of the current flow control period;
105: obtaining the actual transaction amount of various transactions corresponding to the previous flow control period;
106: and putting the weight value and the actual transaction amount of various transactions into a pre-constructed threshold acquisition model to acquire the flow control threshold of the current flow control period.
In an embodiment of the present invention, the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,the actual transaction amount of the j-th transaction received in the i-1-th flow control period is completed.
In an alternative embodiment, the process 102 may also be performed in the following manner, referring to fig. 4, specifically including:
107: the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
108: the method comprises the steps of obtaining the actual completed transaction quantity group of various transactions corresponding to the previous k flow control periods of the current flow control period i, wherein the actual completed transaction quantity group is expressed as follows:
109: putting the weight value group and the actually completed transaction amount group of various transactions into a pre-constructed threshold acquisition model to acquire a flow control threshold of the current flow control period;
in an embodiment of the present invention, the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
Therefore, by taking a plurality of groups of historical data as input data, the reasonable flow control threshold value in the current flow control period can be calculated more accurately.
In the embodiment of the present invention, when the flow control period t=0, the flow control threshold may be set according to a preset ratio, and at this time, the weight value may take 1:
(F d1 ,F d2 ,F d3 ,…)＝1×[λ d1 ,λ d2 ,λ d3 ,…]
in order to calculate a reasonable flow control threshold more accurately, in the embodiment of the invention, the weight value can be acquired by a machine learning mode.
In summary, according to the embodiment of the invention, by self-calculation on each node, the overall risk caused by calculation and distribution of the unified service center is avoided; meanwhile, calculation is carried out on each node based on actual transaction conditions, and under the advantages of more sensitive static flow control and faster recovery speed, the condition that the flow control threshold of a single transaction node is unreasonably set and the whole transaction line is affected is reduced to the greatest extent.
Fig. 5 is a block diagram of a control system 1 for dynamically updating flow control thresholds of a banking system according to one embodiment of the present invention, the control system 1 comprising, with reference to fig. 5: a data obtaining module 11, configured to obtain, for each node, an actual transaction amount of a transaction received by the node in a historical flow control period; the classifying module 12 is used for classifying the transactions and acquiring the actual transaction amount of the various transactions; the threshold value obtaining module 13 is configured to obtain a flow control threshold value of a current flow control period according to the actual transaction amount of each type of transaction through a preset threshold value calculation method; the self-updating module 14 is configured to dynamically update according to the flow control threshold.
In an embodiment of the present invention, the classification module 12 classifies the transaction according to the source of the transaction.
In one embodiment of the present invention, the threshold value acquisition module 13 is configured to:
acquiring a weight value corresponding to the previous flow control period of the current flow control period;
obtaining the actual transaction amount of various transactions corresponding to the previous flow control period;
the weight value and the actual transaction amount of various transactions are put into a pre-constructed threshold acquisition model to acquire a flow control threshold of the current flow control period;
the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,the actual transaction amount of the j-th transaction received in the i-1-th flow control period is completed.
In another embodiment of the present invention, the threshold value acquisition module 13 is configured to:
the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
the method comprises the steps of obtaining the actual completed transaction quantity group of various transactions corresponding to the previous k flow control periods of the current flow control period i, wherein the actual completed transaction quantity group is expressed as follows:
putting the weight value group and the actually completed transaction amount group of various transactions into a pre-constructed threshold acquisition model to acquire a flow control threshold of the current flow control period;
the threshold acquisition model is as follows:
wherein the current period is the ith period, F is the flow control threshold of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
In an embodiment of the invention, the weight value is obtained by means of machine learning.
From the above description of embodiments, it will be apparent to those skilled in the art that the present invention may be implemented in software in combination with a hardware platform. With such understanding, all or part of the technical solution of the present invention contributing to the background art may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in the various embodiments or parts of the embodiments of the present invention.
Therefore, the embodiment of the invention also provides a computer storage medium, which stores a computer program, and the computer storage medium is used for realizing the control method for dynamically updating the flow control threshold value of the bank system provided by the previous embodiment or implementation of the invention when the control method is executed. For example, the storage medium may include a hard disk, a floppy disk, an optical disk, a magnetic tape, a magnetic disk, a flash memory, etc.
The embodiment of the invention also provides a control device for dynamically updating the flow control threshold value of the bank system, which comprises a memory for storing computer readable instructions; and a processor for executing the computer readable instructions to implement the control method for dynamically updating the flow control threshold of the banking system provided by the foregoing embodiment or implementation of the present invention. Optionally, in an implementation manner of the embodiment of the present invention, the apparatus may further include an input/output interface for performing data communication. For example, the device may be a computer, a smart terminal, a server, etc.
The particular embodiments disclosed herein are illustrative only, as the invention may be modified and practiced in equivalent manners apparent to those skilled in the art having the benefit of the teachings herein, so that the specific embodiments of the invention are presented herein by way of example only and the scope of protection is not limited by the details of construction or design disclosed herein except as indicated by the claims. Therefore, the particular exemplary embodiments disclosed above are capable of numerous alternatives, combinations, or modifications, all of which are within the scope of the disclosure herein.
Claims (14)
1. A control method for dynamically updating a flow control threshold of a banking system, the banking system comprising a plurality of system components, each system component performing a different transaction as a node of the banking system, the control method comprising:
for each node, acquiring the actual transaction completion amount of the transaction received by the node in the historical flow control period;
classifying the transactions to obtain the actual transaction amount of all types of transactions;
acquiring a flow control threshold value of a current flow control period according to the actual transaction amount of each type of transaction by a preset threshold value calculation method;
dynamically updating according to the flow control threshold;
the obtaining the flow control threshold value of the current flow control period according to the actual transaction amount of the various transactions by a preset threshold value calculation method comprises the following steps:
acquiring a weight value corresponding to the previous flow control period of the current flow control period;
acquiring the actual transaction amount of the various transactions corresponding to the previous flow control period;
the weight value and the actual transaction amount of all the transactions are put into a pre-constructed threshold value acquisition model, and the flow control threshold value of the current flow control period is acquired;
wherein the threshold acquisition model is as follows:
wherein the current flow control period is the ith period, F is the flow control threshold value of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,the actual completed transaction for the j-th transaction received in the i-1 th flow control periodAmount of the components.
2. The control method of claim 1, wherein said classifying said transaction comprises:
the transactions are categorized according to the different sources of the transactions.
3. The control method of claim 1, wherein the weight value is obtained by means of machine learning.
4. A control method for dynamically updating a flow control threshold of a banking system, the banking system comprising a plurality of system components, each system component performing a different transaction as a node of the banking system, the control method comprising:
for each node, acquiring the actual transaction completion amount of the transaction received by the node in the historical flow control period;
classifying the transactions to obtain the actual transaction amount of all types of transactions;
acquiring a flow control threshold value of a current flow control period according to the actual transaction amount of each type of transaction by a preset threshold value calculation method;
dynamically updating according to the flow control threshold;
the obtaining the flow control threshold value of the current flow control period according to the actual transaction amount of the various transactions by a preset threshold value calculation method comprises the following steps:
the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
the actual transaction amount group of each type of transaction corresponding to the previous k flow control periods of the current flow control period i is obtained, and the actual transaction amount group is expressed as follows:
the weight value group and the actually completed transaction amount group of various transactions are put into a pre-constructed threshold value acquisition model to acquire a flow control threshold value of the current flow control period;
the threshold acquisition model is as follows:
wherein the current flow control period is the ith period, F is the flow control threshold value of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
5. The control method of claim 4, wherein said classifying said transaction comprises:
the transactions are categorized according to the different sources of the transactions.
6. The control method of claim 4, wherein the weight value is obtained by means of machine learning.
7. A control system for dynamically updating a flow control threshold of a banking system, the banking system comprising a plurality of system components, each system component performing a different transaction process as a node of the banking system, the control system comprising:
the data acquisition module is used for acquiring the actual transaction amount of the transaction received by each node in the historical flow control period;
the classification module is used for classifying the transactions and acquiring the actual transaction amount of various transactions;
the threshold value acquisition module is used for acquiring a flow control threshold value of the current flow control period according to the actual transaction amount of the various transactions by a preset threshold value calculation method;
the self-updating module is used for dynamically updating according to the flow control threshold value;
wherein, the threshold value acquisition module is used for:
acquiring a weight value corresponding to the previous flow control period of the current flow control period;
acquiring the actual transaction amount of the various transactions corresponding to the previous flow control period;
the weight value and the actual transaction amount of all the transactions are put into a pre-constructed threshold value acquisition model, and the flow control threshold value of the current flow control period is acquired;
the threshold acquisition model is as follows:
wherein the current flow control period is the ith period, F is the flow control threshold value of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-1 For the weight value corresponding to the i-1 th flow control period,the actual transaction amount of the j-th transaction received in the i-1-th flow control period is completed.
8. The control system of claim 7, wherein the classification module classifies the transaction based on a source of the transaction.
9. The control system of claim 7, wherein the weight value is obtained by means of machine learning.
10. A control system for dynamically updating a flow control threshold of a banking system, the banking system comprising a plurality of system components, each system component performing a different transaction process as a node of the banking system, the control system comprising:
the data acquisition module is used for acquiring the actual transaction amount of the transaction received by each node in the historical flow control period;
the classification module is used for classifying the transactions and acquiring the actual transaction amount of various transactions;
the threshold value acquisition module is used for acquiring a flow control threshold value of the current flow control period according to the actual transaction amount of the various transactions by a preset threshold value calculation method;
the self-updating module is used for dynamically updating according to the flow control threshold value;
wherein, the threshold value acquisition module is used for:
the weight value group corresponding to the previous k flow control periods of the current flow control period i is obtained, and the weight value group is expressed as follows:
(θ Ti-k ,…,θ Ti-3 ,θ Ti-2 ,θ Ti-1) wherein ,
the actual transaction amount group of each type of transaction corresponding to the previous k flow control periods of the current flow control period i is obtained, and the actual transaction amount group is expressed as follows:
the weight value group and the actually completed transaction amount group of various transactions are put into a pre-constructed threshold value acquisition model to acquire a flow control threshold value of the current flow control period;
the threshold acquisition model is as follows:
wherein the current flow control period is the ith period, F is the flow control threshold value of the current flow control period, F dj For the flow control threshold value corresponding to the j-th class transaction, theta Ti-k For the weight corresponding to the k-th flow control period before the current flow control period i,and the actual transaction completion amount of the j-th transaction received in the k-th flow control period before the current flow control period i.
11. The control system of claim 10, wherein the classification module classifies the transaction based on a source of the transaction.
12. The control system of claim 10, wherein the weight value is obtained by means of machine learning.
13. A control device for dynamically updating a flow control threshold of a banking system, comprising a memory and a processor, characterized in that,
the memory is used for storing computer readable instructions;
the processor is configured to execute the computer readable instructions to implement the method of any one of claims 1-6.
14. A computer storage medium storing a computer program which, when executed by a processor, implements the method of any one of claims 1-6.
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